Chronic Obstructive Pulmonary Disease (COPD) is characterized by an irreversible loss of lung function, and is among the leading causes of death worldwide. While it is well established that inhaled pollutants, such as tobacco smoke, can lead to COPD, it is not understood why only 20% of the exposed individuals develop the disease. It is also unclear why some of those who develop the COPD suffer rapid and sever decline of lung function, while others remain relatively stable over time. Such poor understanding of the origin and progression of the disease is a major limitation for the development of effective strategies for both prevention and treatment. The goal of this study is to investigate whether and how innate anatomical features of the airways participate to the disease development. In particular we hypothesize that, in individuals that develop COPD, the anatomical characteristics of the bronchial tree result in air flow patterns that enhance particle deposition, a feature that makes them more susceptible to airway inflammation. To test this hypothesis we will retrospectively explore the lung structure-function relationship in 18 healthy and diseased smokers, by analyzing their airway morphology (reconstructed from CT scans), in relation to the change in lung function over five years. The data is entirely available from the large NIH COPDGene(r) study, from which this study is an Ancillary Study. We will seek two types of predictors of COPD: structural and functional. The structural predictors will be identified by analyzing the subjects' airway morphometry, including branching angle, airway lumen, and airway curvature. The functional predictors will be related to the airflow pattern and associated particle deposition. Because in vivo imaging of flow and deposition in the lungs has limited accuracy and resolution, we will perform virtual inhalation experiments. Physical models of each patient bronchial tree will be 3D printed in synthetic materials and attached to an oscillatory flow circuit. Water will be used as a working fluid, and flow rate and ventilation frequency will be adjusted to compensate for the difference in properties of water with respect to air. MRI measurements will provide the flow velocity map throughout the models at high spatial resolution, and numerical integration of the particle trajectory will provide the deposition pattern. Our innovative approach is made possible by our research team's unique combination of expertise, and by the top-notch resources available at the University of Minnesota Center for Magnetic Resonance Research. If our hypothesis is confirmed, it will pave the way towards early, pre-symptomatic detection of COPD. It will also represent a fundamental step towards an in-depth understanding of local particle deposition, which is necessary to achieve more effective and targeted inhalation drug delivery.